Micro‐seismic Event Detection of Hot Dry Rock based on the Gated Recurrent Unit Model and a Support Vector Machine

2021 ◽  
Vol 95 (6) ◽  
pp. 1940-1947
Author(s):  
Feng SUN ◽  
Haotian HU ◽  
Fa ZHAO ◽  
Xinran YANG ◽  
Zubin CHEN ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Event Detection ◽  
Seismic Event ◽  
Support Vector ◽  
Hot Dry Rock ◽  
Unit Model ◽  
Seismic Event Detection ◽  
Gated Recurrent Unit

Automatic seismic event detection using migration and stacking: a performance and parameter study in Hengill, southwest Iceland

2017 ◽  
Vol 209 (3) ◽  
pp. 1866-1877 ◽  
Author(s):  
F. Wagner ◽  
A. Tryggvason ◽  
R. Roberts ◽  
B. Lund ◽  
Ó. Gudmundsson
Keyword(s):  
Event Detection ◽  
Seismic Event ◽  
Parameter Study ◽  
Seismic Event Detection ◽  
A Performance

scholarly journals Hate Speech Detection for Indonesia Tweets Using Word Embedding And Gated Recurrent Unit

2019 ◽  
Vol 13 (1) ◽  
pp. 43
Author(s):  
Junanda Patihullah ◽  
Edi Winarko
Keyword(s):  
Social Media ◽  
Support Vector Machine ◽  
Feature Extraction ◽  
Deep Learning ◽  
Hate Speech ◽  
Support Vector ◽  
Speech Detection ◽  
The People ◽  
Gated Recurrent Unit ◽  
Rule Out

Social media has changed the people mindset to express thoughts and moods. As the activity of social media users increases, it does not rule out the possibility of crimes of spreading hate speech can spread quickly and widely. So that it is not possible to detect hate speech manually. GRU is one of the deep learning methods that has the ability to learn information relations from the previous time to the present time. In this research feature extraction used is word2vec, because it has the ability to learn semantics between words. In this research the GRU performance will be compared with other supervision methods such as support vector machine, naive bayes, decision tree and logistic regression. The results obtained show that the best accuracy is 92.96% by the GRU model with word2vec feature extraction. The use of word2vec in the comparison supervision method is not good enough from tf and tf-idf.

scholarly journals High-resolution seismic event detection using local similarity for Large-N arrays

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Zefeng Li ◽  
Zhigang Peng ◽  
Dan Hollis ◽  
Lijun Zhu ◽  
James McClellan
Keyword(s):  
High Resolution ◽  
Event Detection ◽  
Seismic Event ◽  
Local Similarity ◽  
Large N ◽  
Seismic Event Detection
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